Millions of users submit queries to search engines and provider or merchant websites every day. Often the users are looking for information that is stored using data formats with well defined attributes such as structured data. Many merchants and providers store information about their products and services as structured data, with tables of attributes having various values associated with the products and services. Examples of structured data include product catalogs, travel databases about hotels, airlines or rental cars databases, and image databases.
While storing information as structured data may make it easier to use the data to populate webpages, catalogs, or to generate reports, the use of structured data may cause problems with respect to traditional keyword based methods for fulfilling queries. In particular, users may generate queries that include features that map only to a subset of the available attributes for a product. For example, a user may submit the query “Nikon Digital Camera.” The query terms “Nikon” and “Digital Camera” can be mapped to attributes associated with product type and brand. However, other attributes associated with the structured data such a color, price, and megapixels have no corresponding mapping in the query. One solution is to fulfill the query using only the mapped attributes and ignore attributes that have not been mapped. However, such a solution may lead to a diminished search experience for a user.